It has its roots in colleges and universities, and that’s where you’re likely to find most MATLAB users today. It’s a high-level programming language normally used for numerical computing, data analysis, and visualization. Unlike Python, MATLAB code is proprietary, which means it’s owned and licensed by someone else for money. Its hallmarks? Python is simple, readable, and easy to use, all with beautifully elegany syntax. Companies use Python for web development, data science, scientific computing, artificial intelligence, computer science, and more as developers create more libraries and functionalities. It’s good for simple tasks that beginners might be interested in, and complex tasks that organizations might want. It’s got a huge and growing functionality. It consistently ranks as one of the most popular languages today. Ever since its inception, Python has only grown more popular. Python was ideated in the late 1980s and was first implemented in December 1989 by Guido van Rossum, Python’s ex Benevolent Dictator for Life. This is one of the major advantages of Python programming over Matlab. Because it’s open-source, anybody can access it, dig around in the guts to see how it works, and even create their own packages for it. Python is an open source programming language used for just about everything. □ History and definitionsīefore we dig into which language is best, it’s worth looking at some historical context. Let’s take a deeper look comparing Python vs MATLAB so you are finally persuaded. But you’re searching for the differences between MATLAB and Python, so clearly you’re not convinced. Python is better than MATLAB in (almost) every situation. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.This is one of those arguments where, outside of a few very specific examples, there’s a clear answer. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. This book will help you build a foundation in machine learning using MATLAB for beginners. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. * Learn feature selection and extraction for dimensionality reduction leading to improved performance. * Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. * Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. * Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. * Discover different ways to transform data using SAS XPORT, import and export tools, * Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. What You Will Learn * Learn the introductory concepts of machine learning. A mathematical and statistical background will really help in following this book well. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. Extract patterns and knowledge from your data in easy way using MATLAB About This Book * Get your first steps into machine learning with the help of this easy-to-follow guide * Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB * Understand how your data works and identify hidden layers in the data with the power of machine learning.
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